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Randall Berry

Publications and source records attributed to Randall Berry.

31 records · Page 2Linked to original sources

Competition among Ride Service Providers with Autonomous Vehicles

Autonomous vehicles (AVs) are attractive for ride service providers (RSPs) in part because they eliminate the need to compete for human drivers. We investigate a scenario where two RSPs with AVs compete for customers. We model the problem as a game where the RSPs select prices for each origin-destination pair over multiple time periods in an underlying graph representing the customers' desired trips. Each RSP also decides the number of AVs to be stationed at each node at each time period to serve the customers' demands. The number of customers who avail of the service of an RSP depends on the price selected by the RSP and its competitor. Since the strategy choices available to an RSP depends on its competitor, we seek to compute a Generalized Nash equilibrium (GNE). We show that there may be multiple GNEs. However, when an RSP selects prices in order to deter its competitor when it is not serving a source-destination pair, the game has a potential function and admits a unique GNE. We also compare the competitive prices with a monopoly price where only one RSP is in the market. Numerically, we show that if a network consists of two equal-size spatial clusters of demand where the demand between clusters is low, the RSPs may partition the market, i.e, one cluster is served by only one RSP. Hence, the competitive price may become close to the monopoly price.

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Price Competition with LTE-U and WiFi

LTE-U is an extension of the Long Term Evolution (LTE) standard for operation in unlicensed spectrum. LTE-U differs from WiFi, the predominant technology used in unlicensed spectrum in that it utilizes a duty cycle mode for accessing the spectrum and allows for a more seamless integration with LTE deployments in licensed spectrum. There have been a number of technical studies on the co-existence of LTE-U and WiFi in unlicensed spectrum In this paper, we instead investigate the impact of such a technology from an economic perspective. We consider a model in which an incumbent service provider (SP) deploys a duty cycle-based technology like LTE-U in an unlicensed band along with operating in a licensed band and competes with one or more entrants that only operate in the unlicensed band using a different technology like WiFi. We characterize the impact of a technology like LTE-U on the market outcome and show that the welfare impacts of this technology are subtle, depending in part on the amount of unlicensed spectrum and number of entrants. The difference in spectral efficiency between LTE and WiFi also plays a role in the competition among SPs. Finally, we investigate the impact of the duty cycle and the portion of unlicensed spectrum used by the technology.

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Quantized VCG Mechanisms for Polymatroid Environments

Many network resource allocation problems can be viewed as allocating a divisible resource, where the allocations are constrained to lie in a polymatroid. We consider market-based mechanisms for such problems. Though the Vickrey-Clarke-Groves (VCG) mechanism can provide the efficient allocation with strong incentive properties (namely dominant strategy incentive compatibility), its well-known high communication requirements can prevent it from being used. There have been a number of approaches for reducing the communication costs of VCG by weakening its incentive properties. Here, instead we take a different approach of reducing communication costs via quantization while maintaining VCG's dominant strategy incentive properties. The cost for this approach is a loss in efficiency which we characterize. We first consider quantizing the resource allocations so that agents need only submit a finite number of bids instead of full utility function. We subsequently consider quantizing the agent's bids.

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Investment in EV charging spots for parking

As demand for electric vehicles (EVs) is expanding, meeting the need for charging infrastructure, especially in urban areas, has become a critical issue. One method of adding charging stations is to install them at parking spots. This increases the value of these spots to EV drivers needing to charge their vehicles. However, there is a cost to constructing these spots and such spots may preclude drivers not needing to charge from using them, reducing the parking options for such drivers\color{black}. We look at two models for how decisions surrounding investment in charging stations on existing parking spots may be undertaken. First, we analyze two firms who compete over installing stations under government set mandates or subsidies. Given the cost of constructing spots and the competitiveness of the markets, we find it is ambiguous whether setting higher mandates or higher subsidies for spot construction leads to better aggregate outcomes. Second, we look at a system operator who faces uncertainty on the size of the EV market. If they are risk neutral, we find a relatively small change in the uncertainty of the EV market can lead to large changes in the optimal charging capacity.

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Competition with Three-Tier Spectrum Access and Spectrum Monitoring

The Citizens Broadband Radio Service (CBRS) recently adopted in the U.S. enables two tiers of commercial users to share spectrum with a third tier of incumbent users. This sharing can be further assisted by Environmental Sensing Capability operators (ESCs), that monitor the spectrum occupancy to determine when use of the spectrum will not harm incumbents. Two key aspects of this framework that impact how firms may compete are the differences in information provided by different ESCs and the different tiers in which a firm may access the spectrum. We develop a game theoretic model that captures both of these features and analyze it to gain insight into their impact. Specifically, we consider a priority access (PA) tier firm has access to the both licensed band and unlicensed band, and a general authorized access (GAA) tier firm has access only to the unlicensed band. The PA tier and GAA tier firms compete for users. Our analysis reveals that the amount of unlicensed and licensed bandwidth in the CBRS must be chosen judiciously in order to maximize the social welfare. We also show that a limited amount of unlicensed access of PA tier firm is beneficial to the user's surplus as well as to the social welfare.

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Fictitious GAN: Training GANs with Historical Models

Generative adversarial networks (GANs) are powerful tools for learning generative models. In practice, the training may suffer from lack of convergence. GANs are commonly viewed as a two-player zero-sum game between two neural networks. Here, we leverage this game theoretic view to study the convergence behavior of the training process. Inspired by the fictitious play learning process, a novel training method, referred to as Fictitious GAN, is introduced. Fictitious GAN trains the deep neural networks using a mixture of historical models. Specifically, the discriminator (resp. generator) is updated according to the best-response to the mixture outputs from a sequence of previously trained generators (resp. discriminators). It is shown that Fictitious GAN can effectively resolve some convergence issues that cannot be resolved by the standard training approach. It is proved that asymptotically the average of the generator outputs has the same distribution as the data samples.

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The impact of bundling licensed and unlicensed wireless service

Unlicensed spectrum has been viewed as a way to increase competition in wireless access and promote innovation in new technologies and business models. However, several recent papers have shown that the openness of such spectrum can also lead to it becoming over congested when used by competing wireless service providers (SPs). This in turn can result in the SPs making no profit and may deter them from entering the market. However, this prior work assumes that unlicensed access is a separate service from any service offered using licensed spectrum. Here, we instead consider the more common case were service providers bundle both licensed and unlicensed spectrum as a single service and offer this with a single price. We analyze a model for such a market and show that in this case SPs are able to gain higher profit than the case without bundling. It is also possible to get higher social welfare with bundling. Moreover, we explore the case where SPs are allowed to manage the customers' average percentage of time they receive service on unlicensed spectrum and characterize the social welfare gap between the profit maximizing and social welfare maximizing setting.

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Joint Transmission with Limited Backhaul Connectivity

Downlink beamforming techniques with low signaling overhead are proposed for joint processing coordinated (JP) multi-point transmission. The objective is to maximize the weighted sum rate within joint transmission clusters. As the considered weighted sum rate maximization is a non-convex problem, successive convex approximation techniques, based on weighted mean-squared error minimization, are applied to devise algorithms with tractable computational complexity. Decentralized algorithms are proposed to enable JP even with limited backhaul connectivity. These algorithms rely provide a variety of alternatives for signaling overhead, computational complexity and convergence behavior. Time division duplexing is exploited to design transceiver training techniques for two scenarios: stream specific estimation and direct estimation. In the stream specific estimation, the base station and user equipment estimate all of the stream specific precoded pilots individually and construct the transmit/receive covariance matrices based on these pilot estimates. With the direct estimation, only the intended transmission is separately estimated and the covariance matrices constructed directly from the aggregate system-wide pilots. The impact of feedback/backhaul signaling quantization is considered, in order to further reduce the signaling overhead. Also, user admission is being considered for time-correlated channels. The enhanced transceiver convergence rate enables periodic beamformer reinitialization, which greatly improves the achieved system performance in dense networks.

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The Value of Sharing Intermittent Spectrum

Recent initiatives by regulatory agencies to increase spectrum resources available for broadband access include rules for sharing spectrum with high-priority incumbents. We study a model in which wireless Service Providers (SPs) charge for access to their own exclusive-use (licensed) band along with access to an additional shared band. The total, or delivered price in each band is the announced price plus a congestion cost, which depends on the load, or total users normalized by the bandwidth. The shared band is intermittently available with some probability, due to incumbent activity, and when unavailable, any traffic carried on that band must be shifted to licensed bands. The SPs then compete for quantity of users. We show that the value of the shared band depends on the relative sizes of the SPs: large SPs with more bandwidth are better able to absorb the variability caused by intermittency than smaller SPs. However, as the amount of shared spectrum increases, the large SPs may not make use of it. In that scenario shared spectrum creates more value than splitting it among the SPs for exclusive use. We also show that fixing the average amount of available shared bandwidth, increasing the reliability of the band is preferable to increasing the bandwidth.

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The value of Side Information in Secondary Spectrum Markets

In a secondary spectrum market primaries set prices for their unused channels to the secondaries. The payoff of a primary depends on the availability of unused channels of its competitors. We consider a model were a primary can acquire its competitor's channel state information (C-CSI) at a cost. We formulate a game between two primaries where each primary decides whether to acquire C-CSI or not and then selects its price based on that. We first characterize the Nash Equilibrium (NE) of this game for a symmetric model where the C-CSI is perfect. We show that the payoff of a primary is independent of the C-CSI acquisition cost. We then generalize our analysis to allow for imperfect estimation and cases where the two primaries have different C-CSI costs or different channel availabilities. Our results show interestingly that the payoff of a primary increases when there is estimation error. We also show that surprisingly, the expected payoff of a primary may decrease when the C-CSI acquisition cost decreases when primaries have different availabilities.

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A Perspective on Future Research Directions in Information Theory

Information theory is rapidly approaching its 70th birthday. What are promising future directions for research in information theory? Where will information theory be having the most impact in 10-20 years? What new and emerging areas are ripe for the most impact, of the sort that information theory has had on the telecommunications industry over the last 60 years? How should the IEEE Information Theory Society promote high-risk new research directions and broaden the reach of information theory, while continuing to be true to its ideals and insisting on the intellectual rigor that makes its breakthroughs so powerful? These are some of the questions that an ad hoc committee (composed of the present authors) explored over the past two years. We have discussed and debated these questions, and solicited detailed inputs from experts in fields including genomics, biology, economics, and neuroscience. This report is the result of these discussions.

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Co-primary inter-operator spectrum sharing over a limited spectrum pool using repeated games

We consider two small cell operators deployed in the same geographical area, sharing spectrum resources from a common pool. A method is investigated to coordinate the utilization of the spectrum pool without monetary transactions and without revealing operator-specific information to other parties. For this, we construct a protocol based on asking and receiving spectrum usage favors by the operators, and keeping a book of the favors. A spectrum usage favor is exchanged between the operators if one is asking for a permission to use some of the resources from the pool on an exclusive basis, and the other is willing to accept that. As a result, the proposed method does not force an operator to take action. An operator with a high load may take spectrum usage favors from an operator that has few users to serve, and it is likely to return these favors in the future to show a cooperative spirit and maintain reciprocity. We formulate the interactions between the operators as a repeated game and determine rules to decide whether to ask or grant a favor at each stage game. We illustrate that under frequent network load variations, which are expected to be prominent in small cell deployments, both operators can attain higher user rates as compared to the case of no coordination of the resource utilization.

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Coordination protocol for inter-operator spectrum sharing in co-primary 5G small cell networks

We consider spectrum sharing between a limited set of operators having similar rights for accessing spectrum. A coordination protocol acting on the level of the Radio Access Network (RAN) is designed. The protocol is non-cooperative, but assumes an agreement to a set of negotiation rules. The signaling overhead is low, and knowledge of competitor's channel state information is not assumed. No monetary transactions are involved; instead, spectrum sharing is based on a RAN-internal virtual currency. The protocol is applicable in a scenario of mutual renting and when the operators form a spectrum pool. The protocol is reactive to variations in interference and load of the operators, and shows gains in a simulated small cell scenario compared to not using any coordination protocol.

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